I have the following:

People decide whether to purchase a good during a given week and I have their final purchase quantity (Min qty = 0 units and Max qty = 10 units observed from the data). Assume I am looking at the results for a particular week. I have multiple demographics variable but two discrete variables are imp namely:

education (=1 if buyer has college degree, 0 otherwise) and

gender (1 = female, 0 = male).

Due to the presence of a large number of 0's and overdispersion, I use a zinb model.

The code I use on Stata:

zinb purchase_qty i.gender##i.educ, inflate (c.age)

The regression results are (not presenting results for the inflation part here):

HTML:

```
purchase_qty Coef. P>|z|
1.gender -0.26 0.028
1.education -0.07 0
gender##education 1 1 0.12 0.027
_cons -0.5 0.56
```

Group1 - gender=0 & educ=0

Group 2 - gender=1 & educ=0

Group3 - gender=0 & educ=1

Group 4 - gender=1 & educ=1.

Could someone please explain how to do this from the above output(taking into account that main effect and interaction effect are significant)?

Thanks.